Spectral-spatial pixel-wise HSIC can be achieved by integrating spatial features into spectral information. For instance, [1]} presented an improved pixel pair feature (PPF) approach called spatial pixel pair feature which is different from traditional PPFs with respect to two main aspects: one is the selection of pixel pair that is only the pixel from the immediate neighborhood of central pixel can be used to make a pair, second is the label of pixel pair would be as of central pixel. To extract discriminative joint representation [2]} introduced a Supervised Spectral-Spatial Residual Network (SSRN) that uses a series of 3D convolutions in the respective spectral and spatial residual blocks. An efficient deep \(3D\) -CNN framework was proposed in [3]} that simultaneously exploits both spectral and spatial information for HSIC.
